索引 (Flink ML : Lib 2.2.0 API)

A B C D E F G H I K L M N O P Q R S T U V W
所有类所有程序包

A

AgglomerativeClustering - org.apache.flink.ml.clustering.agglomerativeclustering中的类: An AlgoOperator that performs a hierarchical clustering using a bottom-up approach.
AgglomerativeClustering() - 类的构造器org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClustering
AgglomerativeClusteringParams<T> - org.apache.flink.ml.clustering.agglomerativeclustering中的接口: Params of AgglomerativeClustering.
ALPHA - 接口中的静态变量org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionParams
ALPHA1 - 接口中的静态变量org.apache.flink.ml.recommendation.swing.SwingParams
ALPHA2 - 接口中的静态变量org.apache.flink.ml.recommendation.swing.SwingParams
ALPHABET_ASC_ORDER - 接口中的静态变量org.apache.flink.ml.feature.stringindexer.StringIndexerParams
ALPHABET_DESC_ORDER - 接口中的静态变量org.apache.flink.ml.feature.stringindexer.StringIndexerParams
ANOVATest - org.apache.flink.ml.stats.anovatest中的类: An AlgoOperator which implements the ANOVA test algorithm.
ANOVATest() - 类的构造器org.apache.flink.ml.stats.anovatest.ANOVATest
ANOVATestParams<T> - org.apache.flink.ml.stats.anovatest中的接口: Params for ANOVATest.
ARBITRARY_ORDER - 接口中的静态变量org.apache.flink.ml.feature.stringindexer.StringIndexerParams
AREA_UNDER_LORENZ - 接口中的静态变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluatorParams
AREA_UNDER_PR - 接口中的静态变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluatorParams
AREA_UNDER_ROC - 接口中的静态变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluatorParams
areaUnderLorenz - 类中的变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinaryMetrics
areaUnderPR - 类中的变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinaryMetrics
areaUnderROC - 类中的变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinaryMetrics
arrayToVector(Object...) - 类中的静态方法org.apache.flink.ml.Functions: Converts a column of arrays of numeric type into a column of DenseVector instances.
ArrayToVectorFunction() - 类的构造器org.apache.flink.ml.Functions.ArrayToVectorFunction

B

BETA - 接口中的静态变量org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionParams
BETA - 接口中的静态变量org.apache.flink.ml.recommendation.swing.SwingParams
Binarizer - org.apache.flink.ml.feature.binarizer中的类: A Transformer that binarizes the columns of continuous features by the given thresholds.
Binarizer() - 类的构造器org.apache.flink.ml.feature.binarizer.Binarizer
BinarizerParams<T> - org.apache.flink.ml.feature.binarizer中的接口: Params of Binarizer.
BINARY - 接口中的静态变量org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelParams
BINARY - 接口中的静态变量org.apache.flink.ml.feature.hashingtf.HashingTFParams: Supported options to decide whether each dimension of the output vector is binary or not.
BinaryClassificationEvaluator - org.apache.flink.ml.evaluation.binaryclassification中的类: An AlgoOperator which calculates the evaluation metrics for binary classification.
BinaryClassificationEvaluator() - 类的构造器org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator
BinaryClassificationEvaluator.BinaryMetrics - org.apache.flink.ml.evaluation.binaryclassification中的类: The evaluation metrics for binary classification.
BinaryClassificationEvaluator.BinarySummary - org.apache.flink.ml.evaluation.binaryclassification中的类: Binary Summary of data in one worker.
BinaryClassificationEvaluatorParams<T> - org.apache.flink.ml.evaluation.binaryclassification中的接口: Params of BinaryClassificationEvaluator.
BinaryLogisticLoss - org.apache.flink.ml.common.lossfunc中的类: The loss function for binary logistic loss.
BinaryMetrics() - 类的构造器org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinaryMetrics
BinaryMetrics(long, double) - 类的构造器org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinaryMetrics
BinarySummary() - 类的构造器org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinarySummary
BinarySummary(Integer, double, long, long) - 类的构造器org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinarySummary
binEdges - 类中的变量org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModelData: The edges of bins for each column, e.g., binEdges[0] is the edges for features at 0-th dimension.
Bucketizer - org.apache.flink.ml.feature.bucketizer中的类: A Transformer that maps multiple columns of continuous features to multiple columns of discrete features, i.e., buckets indices.
Bucketizer() - 类的构造器org.apache.flink.ml.feature.bucketizer.Bucketizer
BucketizerParams<T> - org.apache.flink.ml.feature.bucketizer中的接口: Params for Bucketizer.
BucketizerParams.SplitsArrayValidator - org.apache.flink.ml.feature.bucketizer中的类: Param validator for splitsArray.

C

canEqual(Object) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
CASE_SENSITIVE - 接口中的静态变量org.apache.flink.ml.feature.stopwordsremover.StopWordsRemoverParams
CATEGORICAL - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
categoryMaps - 类中的变量org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData: Index of feature values.
centroids - 类中的变量org.apache.flink.ml.clustering.kmeans.KMeansModelData
ChiSqTest - org.apache.flink.ml.stats.chisqtest中的类: An AlgoOperator which implements the Chi-square test algorithm.
ChiSqTest() - 类的构造器org.apache.flink.ml.stats.chisqtest.ChiSqTest
ChiSqTestParams<T> - org.apache.flink.ml.stats.chisqtest中的接口: Params for ChiSqTest.
coefficient - 类中的变量org.apache.flink.ml.classification.linearsvc.LinearSVCModelData
coefficient - 类中的变量org.apache.flink.ml.regression.linearregression.LinearRegressionModelData
compress() - 类中的方法org.apache.flink.ml.common.util.QuantileSummary: Returns a new summary that compresses the summary statistics and the head buffer.
COMPUTE_FULL_TREE - 接口中的静态变量org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
computeGradient(LabeledPointWithWeight, DenseVector, DenseVector) - 类中的方法org.apache.flink.ml.common.lossfunc.BinaryLogisticLoss
computeGradient(LabeledPointWithWeight, DenseVector, DenseVector) - 类中的方法org.apache.flink.ml.common.lossfunc.HingeLoss
computeGradient(LabeledPointWithWeight, DenseVector, DenseVector) - 类中的方法org.apache.flink.ml.common.lossfunc.LeastSquareLoss
computeGradient(LabeledPointWithWeight, DenseVector, DenseVector) - 接口中的方法org.apache.flink.ml.common.lossfunc.LossFunc: Computes the gradient on the given data point and adds the computed gradient to cumGradient.
computeLoss(LabeledPointWithWeight, DenseVector) - 类中的方法org.apache.flink.ml.common.lossfunc.BinaryLogisticLoss
computeLoss(LabeledPointWithWeight, DenseVector) - 类中的方法org.apache.flink.ml.common.lossfunc.HingeLoss
computeLoss(LabeledPointWithWeight, DenseVector) - 类中的方法org.apache.flink.ml.common.lossfunc.LeastSquareLoss
computeLoss(LabeledPointWithWeight, DenseVector) - 接口中的方法org.apache.flink.ml.common.lossfunc.LossFunc: Computes the loss on the given data point.
CONTINUOUS - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
copy(PriorityQueue<T>) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
copy(PriorityQueue<T>, PriorityQueue<T>) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
copy(DataInputView, DataOutputView) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
count - 类中的变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinaryMetrics
CountVectorizer - org.apache.flink.ml.feature.countvectorizer中的类: An Estimator which converts a collection of text documents to vectors of token counts.
CountVectorizer() - 类的构造器org.apache.flink.ml.feature.countvectorizer.CountVectorizer
CountVectorizerModel - org.apache.flink.ml.feature.countvectorizer中的类: A Model which transforms data using the model data computed by CountVectorizer.
CountVectorizerModel() - 类的构造器org.apache.flink.ml.feature.countvectorizer.CountVectorizerModel
CountVectorizerModelData - org.apache.flink.ml.feature.countvectorizer中的类: Model data of CountVectorizerModel.
CountVectorizerModelData() - 类的构造器org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelData
CountVectorizerModelData(String[]) - 类的构造器org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelData
CountVectorizerModelData.ModelDataDecoder - org.apache.flink.ml.feature.countvectorizer中的类: Decoder for CountVectorizerModelData.
CountVectorizerModelData.ModelDataEncoder - org.apache.flink.ml.feature.countvectorizer中的类: Encoder for CountVectorizerModelData.
CountVectorizerModelParams<T> - org.apache.flink.ml.feature.countvectorizer中的接口: Params for CountVectorizerModel.
CountVectorizerParams<T> - org.apache.flink.ml.feature.countvectorizer中的接口: Params of CountVectorizer.
createInstance() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
createModel(DataStream<Integer>, StreamTableEnvironment) - 类中的方法org.apache.flink.ml.feature.lsh.MinHashLSH
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.classification.knn.KnnModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelDataUtil.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeansModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.idf.IDFModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.imputer.ImputerModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModelData.ModelDataStreamFormat
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData.ModelDataDecoder
createReader(Configuration, FSDataInputStream) - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegressionModelData.ModelDataDecoder
createSerializer(ExecutionConfig) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
createTypeInfo(Type, Map<String, TypeInformation<?>>) - 类中的方法org.apache.flink.ml.common.typeinfo.QuantileSummaryTypeInfoFactory
curNegative - 类中的变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinarySummary
curPositive - 类中的变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinarySummary

D

DCT - org.apache.flink.ml.feature.dct中的类: A Transformer that takes the 1D discrete cosine transform of a real vector.
DCT() - 类的构造器org.apache.flink.ml.feature.dct.DCT
DCTParams<T> - org.apache.flink.ml.feature.dct中的接口: Params for DCT.
DEGREE - 接口中的静态变量org.apache.flink.ml.feature.polynomialexpansion.PolynomialExpansionParams
delta - 类中的变量org.apache.flink.ml.common.util.QuantileSummary.StatsTuple
deserialize(PriorityQueue<T>, DataInputView) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
deserialize(DataInputView) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
DISTANCE_THRESHOLD - 接口中的静态变量org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
docFreq - 类中的变量org.apache.flink.ml.feature.idf.IDFModelData: Document frequency for all terms after filtering out infrequent terms.
DROP_LAST - 接口中的静态变量org.apache.flink.ml.feature.onehotencoder.OneHotEncoderParams
duplicate() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer

E

ElementwiseProduct - org.apache.flink.ml.feature.elementwiseproduct中的类: A Transformer that multiplies each input vector with a given scaling vector using Hadamard product.
ElementwiseProduct() - 类的构造器org.apache.flink.ml.feature.elementwiseproduct.ElementwiseProduct
ElementwiseProductParams<T> - org.apache.flink.ml.feature.elementwiseproduct中的接口: Params of ElementwiseProduct.
encode(Tuple2<Integer, Integer>, OutputStream) - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModelData.ModelDataEncoder
encode(KnnModelData, OutputStream) - 类中的方法org.apache.flink.ml.classification.knn.KnnModelData.ModelDataEncoder
encode(LinearSVCModelData, OutputStream) - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModelData.ModelDataEncoder
encode(LogisticRegressionModelData, OutputStream) - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelDataUtil.ModelDataEncoder
encode(NaiveBayesModelData, OutputStream) - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData.ModelDataEncoder
encode(KMeansModelData, OutputStream) - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeansModelData.ModelDataEncoder
encode(CountVectorizerModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelData.ModelDataEncoder
encode(IDFModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.idf.IDFModelData.ModelDataEncoder
encode(ImputerModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.imputer.ImputerModelData.ModelDataEncoder
encode(KBinsDiscretizerModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModelData.ModelDataEncoder
encode(MinHashLSHModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.lsh.MinHashLSHModelData.ModelDataEncoder
encode(MaxAbsScalerModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModelData.ModelDataEncoder
encode(MinMaxScalerModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData.ModelDataEncoder
encode(RobustScalerModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModelData.ModelDataEncoder
encode(StandardScalerModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerModelData.ModelDataEncoder
encode(StringIndexerModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerModelData.ModelDataEncoder
encode(UnivariateFeatureSelectorModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModelData.ModelDataEncoder
encode(VarianceThresholdSelectorModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData.ModelDataEncoder
encode(VectorIndexerModelData, OutputStream) - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData.ModelDataEncoder
encode(LinearRegressionModelData, OutputStream) - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegressionModelData.ModelDataEncoder
endInput() - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler.MinMaxReduceFunctionOperator
equals(Object) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
equals(Object) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
eval(double[]) - 类中的方法org.apache.flink.ml.Functions.ArrayToVectorFunction
eval(Double[]) - 类中的方法org.apache.flink.ml.Functions.ArrayToVectorFunction
eval(Number[]) - 类中的方法org.apache.flink.ml.Functions.ArrayToVectorFunction
eval(String) - 类中的方法org.apache.flink.ml.feature.tokenizer.Tokenizer.TokenizerUdf
eval(String[]) - 类中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover.RemoveStopWordsFunction
eval(String[], int) - 类中的方法org.apache.flink.ml.feature.ngram.NGram.NGramUdf
eval(String, String, Boolean, boolean, int) - 类中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizer.RegexTokenizerUdf
eval(Vector) - 类中的方法org.apache.flink.ml.Functions.VectorToArrayFunction

F

FDR - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
FEATURE_TYPE - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams: Supported options of the feature type.
FeatureHasher - org.apache.flink.ml.feature.featurehasher中的类: A Transformer that transforms a set of categorical or numerical features into a sparse vector of a specified dimension.
FeatureHasher() - 类的构造器org.apache.flink.ml.feature.featurehasher.FeatureHasher
FeatureHasherParams<T> - org.apache.flink.ml.feature.featurehasher中的接口: Params of FeatureHasher.
featureNormSquares - 类中的变量org.apache.flink.ml.classification.knn.KnnModelData
fit(Table...) - 类中的方法org.apache.flink.ml.classification.knn.Knn
fit(Table...) - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVC
fit(Table...) - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegression
fit(Table...) - 类中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegression
fit(Table...) - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayes
fit(Table...) - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeans
fit(Table...) - 类中的方法org.apache.flink.ml.clustering.kmeans.OnlineKMeans
fit(Table...) - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizer
fit(Table...) - 类中的方法org.apache.flink.ml.feature.idf.IDF
fit(Table...) - 类中的方法org.apache.flink.ml.feature.imputer.Imputer
fit(Table...) - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizer
fit(Table...) - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScaler
fit(Table...) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler
fit(Table...) - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoder
fit(Table...) - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScaler
fit(Table...) - 类中的方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScaler
fit(Table...) - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScaler
fit(Table...) - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexer
fit(Table...) - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelector
fit(Table...) - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelector
fit(Table...) - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexer
fit(Table...) - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegression
FPR - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
FREQUENCY_ASC_ORDER - 接口中的静态变量org.apache.flink.ml.feature.stringindexer.StringIndexerParams
FREQUENCY_DESC_ORDER - 接口中的静态变量org.apache.flink.ml.feature.stringindexer.StringIndexerParams
Functions - org.apache.flink.ml中的类: Built-in table functions for data transformations.
Functions() - 类的构造器org.apache.flink.ml.Functions
Functions.ArrayToVectorFunction - org.apache.flink.ml中的类: A ScalarFunction that converts a column of arrays of numeric type into a column of DenseVector instances.
Functions.VectorToArrayFunction - org.apache.flink.ml中的类: A ScalarFunction that converts a column of Vectors into a column of double arrays.
FValueTest - org.apache.flink.ml.stats.fvaluetest中的类: An AlgoOperator which implements the F-value test algorithm.
FValueTest() - 类的构造器org.apache.flink.ml.stats.fvaluetest.FValueTest
FValueTestParams<T> - org.apache.flink.ml.stats.fvaluetest中的接口: Params for FValueTest.
FWE - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams

G

g - 类中的变量org.apache.flink.ml.common.util.QuantileSummary.StatsTuple
GAPS - 接口中的静态变量org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
generateModelData(int, int, int, long) - 类中的静态方法org.apache.flink.ml.feature.lsh.MinHashLSHModelData
generateRandomModelData(StreamTableEnvironment, int, int) - 类中的静态方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelDataUtil: Generates a Table containing a LogisticRegressionModelData instance with randomly generated coefficient.
generateRandomModelData(StreamTableEnvironment, int, int, double, long) - 类中的静态方法org.apache.flink.ml.clustering.kmeans.KMeansModelData: Generates a Table containing a KMeansModelData instance with randomly generated centroids.
getAlpha() - 接口中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionParams
getAlpha1() - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
getAlpha2() - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
getArity() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
getAvailableLocales() - 类中的静态方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover: Returns a set of all installed locales.
getBeta() - 接口中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionParams
getBeta() - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
getBinary() - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelParams
getBinary() - 接口中的方法org.apache.flink.ml.feature.hashingtf.HashingTFParams
getCaseSensitive() - 接口中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemoverParams
getCompressThreshold() - 类中的方法org.apache.flink.ml.common.util.QuantileSummary
getComputeFullTree() - 接口中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
getCount() - 类中的方法org.apache.flink.ml.common.util.QuantileSummary
getDefaultOrUS() - 类中的静态方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover: Returns system default locale, or Locale.US if the default locale is not in available locales in JVM.
getDegree() - 接口中的方法org.apache.flink.ml.feature.polynomialexpansion.PolynomialExpansionParams
getDistanceThreshold() - 接口中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
getDropLast() - 接口中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderParams
getElementTypeInfo() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
getFeatureType() - 接口中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
getGaps() - 接口中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
getHeadBuffer() - 类中的方法org.apache.flink.ml.common.util.QuantileSummary
getIndices() - 接口中的方法org.apache.flink.ml.feature.vectorslicer.VectorSlicerParams
getInitMode() - 接口中的方法org.apache.flink.ml.clustering.kmeans.KMeansParams
getInputSizes() - 接口中的方法org.apache.flink.ml.feature.vectorassembler.VectorAssemblerParams
getInverse() - 接口中的方法org.apache.flink.ml.feature.dct.DCTParams
getItemCol() - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
getK() - 接口中的方法org.apache.flink.ml.classification.knn.KnnModelParams
getK() - 接口中的方法org.apache.flink.ml.clustering.kmeans.KMeansModelParams
getK() - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
getLabelType() - 接口中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
getLength() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
getLinkage() - 接口中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
getLocale() - 接口中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemoverParams
getLower() - 接口中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerParams
getMax() - 接口中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerParams
getMaxCategories() - 接口中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerParams
getMaxDF() - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerParams
getMaxIndexNum() - 接口中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerParams
getMaxUserBehavior() - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
getMaxUserNumPerItem() - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
getMetricsNames() - 接口中的方法org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluatorParams
getMin() - 接口中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerParams
getMinDF() - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerParams
getMinDocFreq() - 接口中的方法org.apache.flink.ml.feature.idf.IDFParams
getMinTF() - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelParams
getMinTokenLength() - 接口中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
getMinUserBehavior() - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
getMissingValue() - 接口中的方法org.apache.flink.ml.feature.imputer.ImputerModelParams
getModelData() - 类中的方法org.apache.flink.ml.classification.knn.KnnModel
getModelData() - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModel
getModelData() - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModel
getModelData() - 类中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModel
getModelData() - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModel
getModelData() - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeansModel
getModelData() - 类中的方法org.apache.flink.ml.clustering.kmeans.OnlineKMeansModel
getModelData() - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModel
getModelData() - 类中的方法org.apache.flink.ml.feature.idf.IDFModel
getModelData() - 类中的方法org.apache.flink.ml.feature.imputer.ImputerModel
getModelData() - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModel
getModelData() - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModel
getModelData() - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModel
getModelData() - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModel
getModelData() - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModel
getModelData() - 类中的方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScalerModel
getModelData() - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerModel
getModelData() - 类中的方法org.apache.flink.ml.feature.stringindexer.IndexToStringModel
getModelData() - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerModel
getModelData() - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModel
getModelData() - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModel
getModelData() - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModel
getModelData() - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegressionModel
getModelDataByteStream(Table) - 类中的静态方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelDataUtil: Converts the table model to a data stream of bytes.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.classification.knn.KnnModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.classification.linearsvc.LinearSVCModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelDataUtil: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.clustering.kmeans.KMeansModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.idf.IDFModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.imputer.ImputerModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.robustscaler.RobustScalerModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.standardscaler.StandardScalerModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.stringindexer.StringIndexerModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData: Converts the table model to a data stream.
getModelDataStream(Table) - 类中的静态方法org.apache.flink.ml.regression.linearregression.LinearRegressionModelData: Converts the table model to a data stream.
getModelType() - 接口中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModelParams
getModelVersionCol() - 接口中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModelParams
getN() - 接口中的方法org.apache.flink.ml.feature.ngram.NGramParams
getNumBins() - 接口中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
getNumClusters() - 接口中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
getNumHashFunctionsPerTable() - 接口中的方法org.apache.flink.ml.feature.lsh.LSHParams
getNumHashTables() - 接口中的方法org.apache.flink.ml.feature.lsh.LSHParams
getP() - 接口中的方法org.apache.flink.ml.feature.normalizer.NormalizerParams
getParamMap() - 类中的方法org.apache.flink.ml.classification.knn.Knn
getParamMap() - 类中的方法org.apache.flink.ml.classification.knn.KnnModel
getParamMap() - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVC
getParamMap() - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModel
getParamMap() - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegression
getParamMap() - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModel
getParamMap() - 类中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegression
getParamMap() - 类中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModel
getParamMap() - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayes
getParamMap() - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModel
getParamMap() - 类中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClustering
getParamMap() - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeans
getParamMap() - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeansModel
getParamMap() - 类中的方法org.apache.flink.ml.clustering.kmeans.OnlineKMeans
getParamMap() - 类中的方法org.apache.flink.ml.clustering.kmeans.OnlineKMeansModel
getParamMap() - 类中的方法org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator
getParamMap() - 类中的方法org.apache.flink.ml.feature.binarizer.Binarizer
getParamMap() - 类中的方法org.apache.flink.ml.feature.bucketizer.Bucketizer
getParamMap() - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizer
getParamMap() - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.dct.DCT
getParamMap() - 类中的方法org.apache.flink.ml.feature.elementwiseproduct.ElementwiseProduct
getParamMap() - 类中的方法org.apache.flink.ml.feature.featurehasher.FeatureHasher
getParamMap() - 类中的方法org.apache.flink.ml.feature.hashingtf.HashingTF
getParamMap() - 类中的方法org.apache.flink.ml.feature.idf.IDF
getParamMap() - 类中的方法org.apache.flink.ml.feature.idf.IDFModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.imputer.Imputer
getParamMap() - 类中的方法org.apache.flink.ml.feature.imputer.ImputerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.interaction.Interaction
getParamMap() - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizer
getParamMap() - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScaler
getParamMap() - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler
getParamMap() - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.ngram.NGram
getParamMap() - 类中的方法org.apache.flink.ml.feature.normalizer.Normalizer
getParamMap() - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoder
getParamMap() - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.polynomialexpansion.PolynomialExpansion
getParamMap() - 类中的方法org.apache.flink.ml.feature.randomsplitter.RandomSplitter
getParamMap() - 类中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizer
getParamMap() - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScaler
getParamMap() - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.sqltransformer.SQLTransformer
getParamMap() - 类中的方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScaler
getParamMap() - 类中的方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScalerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScaler
getParamMap() - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover
getParamMap() - 类中的方法org.apache.flink.ml.feature.stringindexer.IndexToStringModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexer
getParamMap() - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.tokenizer.Tokenizer
getParamMap() - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelector
getParamMap() - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelector
getParamMap() - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.vectorassembler.VectorAssembler
getParamMap() - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexer
getParamMap() - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModel
getParamMap() - 类中的方法org.apache.flink.ml.feature.vectorslicer.VectorSlicer
getParamMap() - 类中的方法org.apache.flink.ml.recommendation.swing.Swing
getParamMap() - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegression
getParamMap() - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegressionModel
getParamMap() - 类中的方法org.apache.flink.ml.stats.anovatest.ANOVATest
getParamMap() - 类中的方法org.apache.flink.ml.stats.chisqtest.ChiSqTest
getParamMap() - 类中的方法org.apache.flink.ml.stats.fvaluetest.FValueTest
getPattern() - 接口中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
getProducedType() - 类中的方法org.apache.flink.ml.classification.knn.KnnModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelDataUtil.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeansModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.idf.IDFModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.imputer.ImputerModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModelData.ModelDataStreamFormat
getProducedType() - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData.ModelDataDecoder
getProducedType() - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegressionModelData.ModelDataDecoder
getRelativeError() - 类中的方法org.apache.flink.ml.common.util.QuantileSummary
getSampled() - 类中的方法org.apache.flink.ml.common.util.QuantileSummary
getScalingVec() - 接口中的方法org.apache.flink.ml.feature.elementwiseproduct.ElementwiseProductParams
getSelectionMode() - 接口中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
getSelectionThreshold() - 接口中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
getSmoothing() - 接口中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesParams
getSplitsArray() - 接口中的方法org.apache.flink.ml.feature.bucketizer.BucketizerParams
getStatement() - 接口中的方法org.apache.flink.ml.feature.sqltransformer.SQLTransformerParams
getStopWords() - 接口中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemoverParams
getStrategy() - 接口中的方法org.apache.flink.ml.feature.imputer.ImputerParams
getStrategy() - 接口中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
getStringOrderType() - 接口中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerParams
getSubSamples() - 接口中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
getThreshold() - 接口中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModelParams
getThresholds() - 接口中的方法org.apache.flink.ml.feature.binarizer.BinarizerParams
getToLowercase() - 接口中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
getTotalFields() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
getTypeClass() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
getTypeInference(DataTypeFactory) - 类中的方法org.apache.flink.ml.Functions.ArrayToVectorFunction
getTypeInference(DataTypeFactory) - 类中的方法org.apache.flink.ml.Functions.VectorToArrayFunction
getUpper() - 接口中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerParams
getUserCol() - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
getVarianceThreshold() - 接口中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorParams
getVocabularySize() - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerParams
getWeights() - 接口中的方法org.apache.flink.ml.feature.randomsplitter.RandomSplitterParams
getWindows() - 接口中的方法org.apache.flink.ml.common.param.HasWindows
getWithCentering() - 接口中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModelParams
getWithMean() - 接口中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerParams
getWithScaling() - 接口中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModelParams
getWithStd() - 接口中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerParams

H

hashCode() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
hashCode() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
hashFunction(Vector) - 类中的方法org.apache.flink.ml.feature.lsh.MinHashLSHModelData
HashingTF - org.apache.flink.ml.feature.hashingtf中的类: A Transformer that maps a sequence of terms(strings, numbers, booleans) to a sparse vector with a specified dimension using the hashing trick.
HashingTF() - 类的构造器org.apache.flink.ml.feature.hashingtf.HashingTF
HashingTF.HashTFFunction - org.apache.flink.ml.feature.hashingtf中的类: The main logic of HashingTF, which converts the input to a sparse vector.
HashingTFParams<T> - org.apache.flink.ml.feature.hashingtf中的接口: Params of HashingTF.
HashTFFunction(String, boolean, int) - 类的构造器org.apache.flink.ml.feature.hashingtf.HashingTF.HashTFFunction
HasWindows<T> - org.apache.flink.ml.common.param中的接口: Interface for the shared windows param.
HingeLoss - org.apache.flink.ml.common.lossfunc中的类: The loss function for hinge loss.

I

idf - 类中的变量org.apache.flink.ml.feature.idf.IDFModelData: Inverse document frequency for all terms.
IDF - org.apache.flink.ml.feature.idf中的类: An Estimator that computes the inverse document frequency (IDF) for the input documents.
IDF() - 类的构造器org.apache.flink.ml.feature.idf.IDF
IDFModel - org.apache.flink.ml.feature.idf中的类: A Model which transforms data using the model data computed by IDF.
IDFModel() - 类的构造器org.apache.flink.ml.feature.idf.IDFModel
IDFModelData - org.apache.flink.ml.feature.idf中的类: Model data of IDFModel.
IDFModelData() - 类的构造器org.apache.flink.ml.feature.idf.IDFModelData
IDFModelData(DenseVector, long[], long) - 类的构造器org.apache.flink.ml.feature.idf.IDFModelData
IDFModelData.ModelDataDecoder - org.apache.flink.ml.feature.idf中的类: Decoder for IDFModelData.
IDFModelData.ModelDataEncoder - org.apache.flink.ml.feature.idf中的类: Encoder for IDFModelData.
IDFModelParams<T> - org.apache.flink.ml.feature.idf中的接口: Params for IDFModel.
IDFParams<T> - org.apache.flink.ml.feature.idf中的接口: Params for IDF.
Imputer - org.apache.flink.ml.feature.imputer中的类: The imputer for completing missing values of the input columns.
Imputer() - 类的构造器org.apache.flink.ml.feature.imputer.Imputer
ImputerModel - org.apache.flink.ml.feature.imputer中的类: A Model which replaces the missing values using the model data computed by Imputer.
ImputerModel() - 类的构造器org.apache.flink.ml.feature.imputer.ImputerModel
ImputerModelData - org.apache.flink.ml.feature.imputer中的类: Model data of ImputerModel.
ImputerModelData() - 类的构造器org.apache.flink.ml.feature.imputer.ImputerModelData
ImputerModelData(Map<String, Double>) - 类的构造器org.apache.flink.ml.feature.imputer.ImputerModelData
ImputerModelData.ModelDataDecoder - org.apache.flink.ml.feature.imputer中的类: Decoder for ImputerModelData.
ImputerModelData.ModelDataEncoder - org.apache.flink.ml.feature.imputer中的类: Encoder for ImputerModelData.
ImputerModelParams<T> - org.apache.flink.ml.feature.imputer中的接口: Params for ImputerModel.
ImputerParams<T> - org.apache.flink.ml.feature.imputer中的接口: Params of Imputer.
IndexToStringModel - org.apache.flink.ml.feature.stringindexer中的类: A Model which transforms input index column(s) to string column(s) using the model data computed by StringIndexer.
IndexToStringModel() - 类的构造器org.apache.flink.ml.feature.stringindexer.IndexToStringModel
IndexToStringModelParams<T> - org.apache.flink.ml.feature.stringindexer中的接口: Params for IndexToStringModel.
indices - 类中的变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModelData: Indices of the input features that are selected.
indices - 类中的变量org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData
INDICES - 接口中的静态变量org.apache.flink.ml.feature.vectorslicer.VectorSlicerParams
indicesValidator() - 接口中的静态方法org.apache.flink.ml.feature.vectorslicer.VectorSlicerParams
INIT_MODE - 接口中的静态变量org.apache.flink.ml.clustering.kmeans.KMeansParams
initializeState(StateInitializationContext) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler.MinMaxReduceFunctionOperator
INPUT_SIZES - 接口中的静态变量org.apache.flink.ml.feature.vectorassembler.VectorAssemblerParams
insert(double) - 类中的方法org.apache.flink.ml.common.util.QuantileSummary: Insert a new observation into the summary.
INSTANCE - 类中的静态变量org.apache.flink.ml.common.lossfunc.BinaryLogisticLoss
INSTANCE - 类中的静态变量org.apache.flink.ml.common.lossfunc.HingeLoss
INSTANCE - 类中的静态变量org.apache.flink.ml.common.lossfunc.LeastSquareLoss
Interaction - org.apache.flink.ml.feature.interaction中的类: A Transformer that takes vector or numerical columns, and generates a single vector column that contains the product of all combinations of one value from each input column.
Interaction() - 类的构造器org.apache.flink.ml.feature.interaction.Interaction
InteractionParams<T> - org.apache.flink.ml.feature.interaction中的接口: Params of Interaction.
INVERSE - 接口中的静态变量org.apache.flink.ml.feature.dct.DCTParams
isBasicType() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
isCompressed() - 类中的方法org.apache.flink.ml.common.util.QuantileSummary
isEmpty() - 类中的方法org.apache.flink.ml.common.util.QuantileSummary: Checks whether the QuantileSummary has inserted rows.
isImmutableType() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
isKeyType() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
isTupleType() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
ITEM_COL - 接口中的静态变量org.apache.flink.ml.recommendation.swing.SwingParams

K

K - 接口中的静态变量org.apache.flink.ml.classification.knn.KnnModelParams
K - 接口中的静态变量org.apache.flink.ml.clustering.kmeans.KMeansModelParams
K - 接口中的静态变量org.apache.flink.ml.recommendation.swing.SwingParams
KBinsDiscretizer - org.apache.flink.ml.feature.kbinsdiscretizer中的类: An Estimator which implements discretization (also known as quantization or binning) to transform continuous features into discrete ones.
KBinsDiscretizer() - 类的构造器org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizer
KBinsDiscretizerModel - org.apache.flink.ml.feature.kbinsdiscretizer中的类: A Model which transforms continuous features into discrete features using the model data computed by KBinsDiscretizer.
KBinsDiscretizerModel() - 类的构造器org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModel
KBinsDiscretizerModelData - org.apache.flink.ml.feature.kbinsdiscretizer中的类: Model data of KBinsDiscretizerModel.
KBinsDiscretizerModelData() - 类的构造器org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModelData
KBinsDiscretizerModelData(double[][]) - 类的构造器org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModelData
KBinsDiscretizerModelData.ModelDataDecoder - org.apache.flink.ml.feature.kbinsdiscretizer中的类: Decoder for KBinsDiscretizerModelData.
KBinsDiscretizerModelData.ModelDataEncoder - org.apache.flink.ml.feature.kbinsdiscretizer中的类: Encoder for KBinsDiscretizerModelData.
KBinsDiscretizerModelParams<T> - org.apache.flink.ml.feature.kbinsdiscretizer中的接口: Params for KBinsDiscretizerModel.
KBinsDiscretizerParams<T> - org.apache.flink.ml.feature.kbinsdiscretizer中的接口: Params for KBinsDiscretizer.
keyDistance(Vector, Vector) - 类中的方法org.apache.flink.ml.feature.lsh.MinHashLSHModelData
KMeans - org.apache.flink.ml.clustering.kmeans中的类: An Estimator which implements the k-means clustering algorithm.
KMeans() - 类的构造器org.apache.flink.ml.clustering.kmeans.KMeans
KMEANS - 接口中的静态变量org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
KMeansModel - org.apache.flink.ml.clustering.kmeans中的类: A Model which clusters data into k clusters using the model data computed by KMeans.
KMeansModel() - 类的构造器org.apache.flink.ml.clustering.kmeans.KMeansModel
KMeansModelData - org.apache.flink.ml.clustering.kmeans中的类: Model data of KMeansModel and OnlineKMeansModel.
KMeansModelData() - 类的构造器org.apache.flink.ml.clustering.kmeans.KMeansModelData
KMeansModelData(DenseVector[], DenseVector) - 类的构造器org.apache.flink.ml.clustering.kmeans.KMeansModelData
KMeansModelData.ModelDataDecoder - org.apache.flink.ml.clustering.kmeans中的类: Data decoder for KMeansModelData.
KMeansModelData.ModelDataEncoder - org.apache.flink.ml.clustering.kmeans中的类: Data encoder for KMeansModelData.
KMeansModelParams<T> - org.apache.flink.ml.clustering.kmeans中的接口: Params of KMeansModel and OnlineKMeansModel.
KMeansParams<T> - org.apache.flink.ml.clustering.kmeans中的接口: Params of KMeans.
Knn - org.apache.flink.ml.classification.knn中的类: An Estimator which implements the KNN algorithm.
Knn() - 类的构造器org.apache.flink.ml.classification.knn.Knn
KnnModel - org.apache.flink.ml.classification.knn中的类: A Model which classifies data using the model data computed by Knn.
KnnModel() - 类的构造器org.apache.flink.ml.classification.knn.KnnModel
KnnModelData - org.apache.flink.ml.classification.knn中的类: Model data of KnnModel.
KnnModelData() - 类的构造器org.apache.flink.ml.classification.knn.KnnModelData
KnnModelData(DenseMatrix, DenseVector, DenseVector) - 类的构造器org.apache.flink.ml.classification.knn.KnnModelData
KnnModelData.ModelDataDecoder - org.apache.flink.ml.classification.knn中的类: Decoder for KnnModelData.
KnnModelData.ModelDataEncoder - org.apache.flink.ml.classification.knn中的类: Encoder for KnnModelData.
KnnModelParams<T> - org.apache.flink.ml.classification.knn中的接口: Params for KnnModel.
KnnParams<T> - org.apache.flink.ml.classification.knn中的接口: Params for Knn.
ks - 类中的变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinaryMetrics
KS - 接口中的静态变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluatorParams

L

LABEL_TYPE - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams: Supported options of the label type.
labels - 类中的变量org.apache.flink.ml.classification.knn.KnnModelData
labels - 类中的变量org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData: Value of labels.
LeastSquareLoss - org.apache.flink.ml.common.lossfunc中的类: The loss function for least square loss.
LinearRegression - org.apache.flink.ml.regression.linearregression中的类: An Estimator which implements the linear regression algorithm.
LinearRegression() - 类的构造器org.apache.flink.ml.regression.linearregression.LinearRegression
LinearRegressionModel - org.apache.flink.ml.regression.linearregression中的类: A Model which predicts data using the model data computed by LinearRegression.
LinearRegressionModel() - 类的构造器org.apache.flink.ml.regression.linearregression.LinearRegressionModel
LinearRegressionModelData - org.apache.flink.ml.regression.linearregression中的类: Model data of LinearRegressionModel.
LinearRegressionModelData() - 类的构造器org.apache.flink.ml.regression.linearregression.LinearRegressionModelData
LinearRegressionModelData(DenseVector) - 类的构造器org.apache.flink.ml.regression.linearregression.LinearRegressionModelData
LinearRegressionModelData.ModelDataDecoder - org.apache.flink.ml.regression.linearregression中的类: Data decoder for LinearRegressionModel.
LinearRegressionModelData.ModelDataEncoder - org.apache.flink.ml.regression.linearregression中的类: Data encoder for LinearRegressionModel.
LinearRegressionModelParams<T> - org.apache.flink.ml.regression.linearregression中的接口: Params for LinearRegressionModel.
LinearRegressionParams<T> - org.apache.flink.ml.regression.linearregression中的接口: Params for LinearRegression.
LinearSVC - org.apache.flink.ml.classification.linearsvc中的类: An Estimator which implements the linear support vector classification.
LinearSVC() - 类的构造器org.apache.flink.ml.classification.linearsvc.LinearSVC
LinearSVCModel - org.apache.flink.ml.classification.linearsvc中的类: A Model which classifies data using the model data computed by LinearSVC.
LinearSVCModel() - 类的构造器org.apache.flink.ml.classification.linearsvc.LinearSVCModel
LinearSVCModelData - org.apache.flink.ml.classification.linearsvc中的类: Model data of LinearSVCModel.
LinearSVCModelData() - 类的构造器org.apache.flink.ml.classification.linearsvc.LinearSVCModelData
LinearSVCModelData(DenseVector) - 类的构造器org.apache.flink.ml.classification.linearsvc.LinearSVCModelData
LinearSVCModelData.ModelDataDecoder - org.apache.flink.ml.classification.linearsvc中的类: Data decoder for LinearSVCModel.
LinearSVCModelData.ModelDataEncoder - org.apache.flink.ml.classification.linearsvc中的类: Data encoder for LinearSVCModel.
LinearSVCModelParams<T> - org.apache.flink.ml.classification.linearsvc中的接口: Params for LinearSVCModel.
LinearSVCParams<T> - org.apache.flink.ml.classification.linearsvc中的接口: Params for LinearSVC.
LINKAGE - 接口中的静态变量org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams: Supported options to compute the distance between two clusters.
LINKAGE_AVERAGE - 接口中的静态变量org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
LINKAGE_COMPLETE - 接口中的静态变量org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
LINKAGE_SINGLE - 接口中的静态变量org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
LINKAGE_WARD - 接口中的静态变量org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.knn.Knn
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.knn.KnnModel: Loads model data from path.
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.linearsvc.LinearSVC
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.linearsvc.LinearSVCModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.logisticregression.LogisticRegression
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegression
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.naivebayes.NaiveBayes
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClustering
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.clustering.kmeans.KMeans
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.clustering.kmeans.KMeansModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.clustering.kmeans.OnlineKMeans
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.clustering.kmeans.OnlineKMeansModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.binarizer.Binarizer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.bucketizer.Bucketizer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.countvectorizer.CountVectorizer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.dct.DCT
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.elementwiseproduct.ElementwiseProduct
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.featurehasher.FeatureHasher
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.hashingtf.HashingTF
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.idf.IDF
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.idf.IDFModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.imputer.Imputer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.imputer.ImputerModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.interaction.Interaction
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.lsh.MinHashLSH
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.lsh.MinHashLSHModel: Loads model data from path.
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScaler
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModel: Loads model data from path.
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModel: Loads model data from path.
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.ngram.NGram
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.normalizer.Normalizer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoder
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.polynomialexpansion.PolynomialExpansion
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.randomsplitter.RandomSplitter
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.robustscaler.RobustScaler
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.robustscaler.RobustScalerModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.sqltransformer.SQLTransformer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScaler
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScalerModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.standardscaler.StandardScaler
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.standardscaler.StandardScalerModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.stringindexer.IndexToStringModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.stringindexer.StringIndexer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.stringindexer.StringIndexerModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.tokenizer.Tokenizer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelector
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelector
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.vectorassembler.VectorAssembler
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.vectorindexer.VectorIndexer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.feature.vectorslicer.VectorSlicer
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.recommendation.swing.Swing
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.regression.linearregression.LinearRegression
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.regression.linearregression.LinearRegressionModel
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.stats.anovatest.ANOVATest
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.stats.chisqtest.ChiSqTest
load(StreamTableEnvironment, String) - 类中的静态方法org.apache.flink.ml.stats.fvaluetest.FValueTest
loadDefaultStopWords(String) - 类中的静态方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover: Loads the default stop words for the given language.
loadServable(String) - 类中的静态方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModel
LOCALE - 接口中的静态变量org.apache.flink.ml.feature.stopwordsremover.StopWordsRemoverParams
LogisticRegression - org.apache.flink.ml.classification.logisticregression中的类: An Estimator which implements the logistic regression algorithm.
LogisticRegression() - 类的构造器org.apache.flink.ml.classification.logisticregression.LogisticRegression
LogisticRegressionModel - org.apache.flink.ml.classification.logisticregression中的类: A Model which classifies data using the model data computed by LogisticRegression.
LogisticRegressionModel() - 类的构造器org.apache.flink.ml.classification.logisticregression.LogisticRegressionModel
LogisticRegressionModelDataUtil - org.apache.flink.ml.classification.logisticregression中的类: The utility class which provides methods to convert model data from Table to Datastream, and classes to save/load model data.
LogisticRegressionModelDataUtil() - 类的构造器org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelDataUtil
LogisticRegressionModelDataUtil.ModelDataDecoder - org.apache.flink.ml.classification.logisticregression中的类: Data decoder for LogisticRegression and OnlineLogisticRegression.
LogisticRegressionModelDataUtil.ModelDataEncoder - org.apache.flink.ml.classification.logisticregression中的类: Data encoder for LogisticRegression and OnlineLogisticRegression.
LogisticRegressionParams<T> - org.apache.flink.ml.classification.logisticregression中的接口: Params for LogisticRegression.
LossFunc - org.apache.flink.ml.common.lossfunc中的接口: A loss function is to compute the loss and gradient with the given coefficient and training data.
LOWER - 接口中的静态变量org.apache.flink.ml.feature.robustscaler.RobustScalerParams
LSHModelParams<T> - org.apache.flink.ml.feature.lsh中的接口: Params for LSHModel.
LSHParams<T> - org.apache.flink.ml.feature.lsh中的接口: Params for LSH.

M

map(Row) - 类中的方法org.apache.flink.ml.feature.hashingtf.HashingTF.HashTFFunction
MAX - 接口中的静态变量org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerParams
MAX_CATEGORIES - 接口中的静态变量org.apache.flink.ml.feature.vectorindexer.VectorIndexerParams
MAX_DF - 接口中的静态变量org.apache.flink.ml.feature.countvectorizer.CountVectorizerParams
MAX_INDEX_NUM - 接口中的静态变量org.apache.flink.ml.feature.stringindexer.StringIndexerParams
MAX_USER_BEHAVIOR - 接口中的静态变量org.apache.flink.ml.recommendation.swing.SwingParams
MAX_USER_NUM_PER_ITEM - 接口中的静态变量org.apache.flink.ml.recommendation.swing.SwingParams
MaxAbsScaler - org.apache.flink.ml.feature.maxabsscaler中的类: An Estimator which implements the MaxAbsScaler algorithm.
MaxAbsScaler() - 类的构造器org.apache.flink.ml.feature.maxabsscaler.MaxAbsScaler
MaxAbsScalerModel - org.apache.flink.ml.feature.maxabsscaler中的类: A Model which transforms data using the model data computed by MaxAbsScaler.
MaxAbsScalerModel() - 类的构造器org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModel
MaxAbsScalerModelData - org.apache.flink.ml.feature.maxabsscaler中的类: Model data of MaxAbsScalerModel.
MaxAbsScalerModelData() - 类的构造器org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModelData
MaxAbsScalerModelData(DenseVector) - 类的构造器org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModelData
MaxAbsScalerModelData.ModelDataDecoder - org.apache.flink.ml.feature.maxabsscaler中的类: Decoder for MaxAbsScalerModelData.
MaxAbsScalerModelData.ModelDataEncoder - org.apache.flink.ml.feature.maxabsscaler中的类: Encoder for MaxAbsScalerModelData.
MaxAbsScalerParams<T> - org.apache.flink.ml.feature.maxabsscaler中的接口: Params for MaxAbsScaler.
maxScore - 类中的变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinarySummary
maxVector - 类中的变量org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModelData
maxVector - 类中的变量org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData
mean - 类中的变量org.apache.flink.ml.feature.standardscaler.StandardScalerModelData: Mean of each dimension.
MEAN - 接口中的静态变量org.apache.flink.ml.feature.imputer.ImputerParams
MEDIAN - 接口中的静态变量org.apache.flink.ml.feature.imputer.ImputerParams
medians - 类中的变量org.apache.flink.ml.feature.robustscaler.RobustScalerModelData
merge(QuantileSummary) - 类中的方法org.apache.flink.ml.common.util.QuantileSummary: Merges two summaries together.
merge(BinaryClassificationEvaluator.BinaryMetrics) - 类中的方法org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinaryMetrics
METRICS_NAMES - 接口中的静态变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluatorParams: Param for supported metric names in binary classification evaluation (supports 'areaUnderROC', 'areaUnderPR', 'ks' and 'areaUnderLorenz').
MIN - 接口中的静态变量org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerParams
MIN_DF - 接口中的静态变量org.apache.flink.ml.feature.countvectorizer.CountVectorizerParams
MIN_DOC_FREQ - 接口中的静态变量org.apache.flink.ml.feature.idf.IDFParams
MIN_TF - 接口中的静态变量org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelParams
MIN_TOKEN_LENGTH - 接口中的静态变量org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
MIN_USER_BEHAVIOR - 接口中的静态变量org.apache.flink.ml.recommendation.swing.SwingParams
MinHashLSH - org.apache.flink.ml.feature.lsh中的类: An Estimator that implements the MinHash LSH algorithm, which supports LSH for Jaccard distance.
MinHashLSH() - 类的构造器org.apache.flink.ml.feature.lsh.MinHashLSH
MinHashLSHModel - org.apache.flink.ml.feature.lsh中的类: A Model which generates hash values using the model data computed by MinHashLSH.
MinHashLSHModel() - 类的构造器org.apache.flink.ml.feature.lsh.MinHashLSHModel
MinHashLSHModelData - org.apache.flink.ml.feature.lsh中的类: Model data of MinHashLSHModel.
MinHashLSHModelData() - 类的构造器org.apache.flink.ml.feature.lsh.MinHashLSHModelData
MinHashLSHModelData(int, int, int[], int[]) - 类的构造器org.apache.flink.ml.feature.lsh.MinHashLSHModelData
MinHashLSHModelData.ModelDataEncoder - org.apache.flink.ml.feature.lsh中的类: Encoder for MinHashLSHModelData.
MinHashLSHParams<T> - org.apache.flink.ml.feature.lsh中的接口: Params for MinHashLSH.
MinMaxReduceFunctionOperator() - 类的构造器org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler.MinMaxReduceFunctionOperator
MinMaxScaler - org.apache.flink.ml.feature.minmaxscaler中的类: An Estimator which implements the MinMaxScaler algorithm.
MinMaxScaler() - 类的构造器org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler
MinMaxScaler.MinMaxReduceFunctionOperator - org.apache.flink.ml.feature.minmaxscaler中的类: A stream operator to compute the min and max values in each partition of the input bounded data stream.
MinMaxScalerModel - org.apache.flink.ml.feature.minmaxscaler中的类: A Model which transforms data using the model data computed by MinMaxScaler.
MinMaxScalerModel() - 类的构造器org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModel
MinMaxScalerModelData - org.apache.flink.ml.feature.minmaxscaler中的类: Model data of MinMaxScalerModel.
MinMaxScalerModelData() - 类的构造器org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData
MinMaxScalerModelData(DenseVector, DenseVector) - 类的构造器org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData
MinMaxScalerModelData.ModelDataDecoder - org.apache.flink.ml.feature.minmaxscaler中的类: Decoder for MinMaxScalerModelData.
MinMaxScalerModelData.ModelDataEncoder - org.apache.flink.ml.feature.minmaxscaler中的类: Encoder for MinMaxScalerModelData.
MinMaxScalerParams<T> - org.apache.flink.ml.feature.minmaxscaler中的接口: Params for MinMaxScaler.
minVector - 类中的变量org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData
MISSING_VALUE - 接口中的静态变量org.apache.flink.ml.feature.imputer.ImputerModelParams
MODEL_DATA_VERSION_GAUGE_KEY - 类中的静态变量org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModel
MODEL_DATA_VERSION_GAUGE_KEY - 类中的静态变量org.apache.flink.ml.clustering.kmeans.OnlineKMeansModel
MODEL_TYPE - 接口中的静态变量org.apache.flink.ml.classification.naivebayes.NaiveBayesModelParams
MODEL_VERSION_COL - 接口中的静态变量org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModelParams
ModelDataDecoder() - 类的构造器org.apache.flink.ml.classification.knn.KnnModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.classification.linearsvc.LinearSVCModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelDataUtil.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.clustering.kmeans.KMeansModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.idf.IDFModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.imputer.ImputerModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.robustscaler.RobustScalerModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.standardscaler.StandardScalerModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.stringindexer.StringIndexerModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData.ModelDataDecoder
ModelDataDecoder() - 类的构造器org.apache.flink.ml.regression.linearregression.LinearRegressionModelData.ModelDataDecoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.classification.knn.KnnModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.classification.linearsvc.LinearSVCModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.classification.logisticregression.LogisticRegressionModelDataUtil.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.clustering.kmeans.KMeansModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.idf.IDFModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.imputer.ImputerModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.lsh.MinHashLSHModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.robustscaler.RobustScalerModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.standardscaler.StandardScalerModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.stringindexer.StringIndexerModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData.ModelDataEncoder
ModelDataEncoder() - 类的构造器org.apache.flink.ml.regression.linearregression.LinearRegressionModelData.ModelDataEncoder
ModelDataStreamFormat() - 类的构造器org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModelData.ModelDataStreamFormat
MOST_FREQUENT - 接口中的静态变量org.apache.flink.ml.feature.imputer.ImputerParams

N

N - 接口中的静态变量org.apache.flink.ml.feature.ngram.NGramParams
NaiveBayes - org.apache.flink.ml.classification.naivebayes中的类: An Estimator which implements the naive bayes classification algorithm.
NaiveBayes() - 类的构造器org.apache.flink.ml.classification.naivebayes.NaiveBayes
NaiveBayesModel - org.apache.flink.ml.classification.naivebayes中的类: A Model which classifies data using the model data computed by NaiveBayes.
NaiveBayesModel() - 类的构造器org.apache.flink.ml.classification.naivebayes.NaiveBayesModel
NaiveBayesModelData - org.apache.flink.ml.classification.naivebayes中的类: Model data of NaiveBayesModel.
NaiveBayesModelData() - 类的构造器org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData
NaiveBayesModelData(Map<Double, Double>[][], DenseVector, DenseVector) - 类的构造器org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData
NaiveBayesModelData.ModelDataDecoder - org.apache.flink.ml.classification.naivebayes中的类: Data decoder for the NaiveBayesModelData.
NaiveBayesModelData.ModelDataEncoder - org.apache.flink.ml.classification.naivebayes中的类: Data encoder for the NaiveBayesModelData.
NaiveBayesModelParams<T> - org.apache.flink.ml.classification.naivebayes中的接口: Params of NaiveBayesModel.
NaiveBayesParams<T> - org.apache.flink.ml.classification.naivebayes中的接口: Params of NaiveBayes.
NGram - org.apache.flink.ml.feature.ngram中的类: A Transformer that converts the input string array into an array of n-grams, where each n-gram is represented by a space-separated string of words.
NGram() - 类的构造器org.apache.flink.ml.feature.ngram.NGram
NGram.NGramUdf - org.apache.flink.ml.feature.ngram中的类: The main logic of NGram, which converts the input string array to an array of n-grams.
NGramParams<T> - org.apache.flink.ml.feature.ngram中的接口: Params of NGram.
NGramUdf() - 类的构造器org.apache.flink.ml.feature.ngram.NGram.NGramUdf
Normalizer - org.apache.flink.ml.feature.normalizer中的类: A Transformer that normalizes a vector to have unit norm using the given p-norm.
Normalizer() - 类的构造器org.apache.flink.ml.feature.normalizer.Normalizer
NormalizerParams<T> - org.apache.flink.ml.feature.normalizer中的接口: Params of Normalizer.
NUM_BINS - 接口中的静态变量org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
NUM_CLUSTERS - 接口中的静态变量org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
NUM_HASH_FUNCTIONS_PER_TABLE - 接口中的静态变量org.apache.flink.ml.feature.lsh.LSHParams: Param for the number of hash functions per hash table used in LSH AND-amplification.
NUM_HASH_TABLES - 接口中的静态变量org.apache.flink.ml.feature.lsh.LSHParams: Param for the number of hash tables used in LSH OR-amplification.
NUM_TOP_FEATURES - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
numDocs - 类中的变量org.apache.flink.ml.feature.idf.IDFModelData: Number of docs in the training set.
numHashFunctionsPerTable - 类中的变量org.apache.flink.ml.feature.lsh.MinHashLSHModelData
numHashTables - 类中的变量org.apache.flink.ml.feature.lsh.MinHashLSHModelData
numOfFeatures - 类中的变量org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData

O

OneHotEncoder - org.apache.flink.ml.feature.onehotencoder中的类: An Estimator which implements the one-hot encoding algorithm.
OneHotEncoder() - 类的构造器org.apache.flink.ml.feature.onehotencoder.OneHotEncoder
OneHotEncoderModel - org.apache.flink.ml.feature.onehotencoder中的类: A Model which encodes data into one-hot format using the model data computed by OneHotEncoder.
OneHotEncoderModel() - 类的构造器org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModel
OneHotEncoderModelData - org.apache.flink.ml.feature.onehotencoder中的类: Model data of OneHotEncoderModel.
OneHotEncoderModelData() - 类的构造器org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModelData
OneHotEncoderModelData.ModelDataEncoder - org.apache.flink.ml.feature.onehotencoder中的类: Data encoder for the OneHotEncoder model data.
OneHotEncoderModelData.ModelDataStreamFormat - org.apache.flink.ml.feature.onehotencoder中的类: Data decoder for the OneHotEncoder model data.
OneHotEncoderParams<T> - org.apache.flink.ml.feature.onehotencoder中的接口: Params of OneHotEncoderModel.
OnlineKMeans - org.apache.flink.ml.clustering.kmeans中的类: OnlineKMeans extends the function of KMeans, supporting to train a K-Means model continuously according to an unbounded stream of train data.
OnlineKMeans() - 类的构造器org.apache.flink.ml.clustering.kmeans.OnlineKMeans
OnlineKMeansModel - org.apache.flink.ml.clustering.kmeans中的类: OnlineKMeansModel can be regarded as an advanced KMeansModel operator which can update model data in a streaming format, using the model data provided by OnlineKMeans.
OnlineKMeansModel() - 类的构造器org.apache.flink.ml.clustering.kmeans.OnlineKMeansModel
OnlineKMeansParams<T> - org.apache.flink.ml.clustering.kmeans中的接口: Params of OnlineKMeans.
OnlineLogisticRegression - org.apache.flink.ml.classification.logisticregression中的类: An Estimator which implements the online logistic regression algorithm.
OnlineLogisticRegression() - 类的构造器org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegression
OnlineLogisticRegressionModel - org.apache.flink.ml.classification.logisticregression中的类: A Model which classifies data using the model data computed by OnlineLogisticRegression.
OnlineLogisticRegressionModel() - 类的构造器org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModel
OnlineLogisticRegressionModelParams<T> - org.apache.flink.ml.classification.logisticregression中的接口: Params for OnlineLogisticRegressionModel.
OnlineLogisticRegressionParams<T> - org.apache.flink.ml.classification.logisticregression中的接口: Params of OnlineLogisticRegression.
OnlineStandardScaler - org.apache.flink.ml.feature.standardscaler中的类: An Estimator which implements the online standard scaling algorithm, which is the online version of StandardScaler.
OnlineStandardScaler() - 类的构造器org.apache.flink.ml.feature.standardscaler.OnlineStandardScaler
OnlineStandardScalerModel - org.apache.flink.ml.feature.standardscaler中的类: A Model which transforms data using the model data computed by OnlineStandardScaler.
OnlineStandardScalerModel() - 类的构造器org.apache.flink.ml.feature.standardscaler.OnlineStandardScalerModel
OnlineStandardScalerModelParams<T> - org.apache.flink.ml.feature.standardscaler中的接口: Params for OnlineStandardScalerModel.
OnlineStandardScalerParams<T> - org.apache.flink.ml.feature.standardscaler中的接口: Params for OnlineStandardScaler.
open(FunctionContext) - 类中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover.RemoveStopWordsFunction
optimize(DataStream<DenseVector>, DataStream<LabeledPointWithWeight>, LossFunc) - 接口中的方法org.apache.flink.ml.common.optimizer.Optimizer: Optimizes the given loss function using the initial model data and the bounded training data.
optimize(DataStream<DenseVector>, DataStream<LabeledPointWithWeight>, LossFunc) - 类中的方法org.apache.flink.ml.common.optimizer.SGD
Optimizer - org.apache.flink.ml.common.optimizer中的接口: An optimizer is a function to modify the weight of a machine learning model, which aims to find the optimal parameter configuration for a machine learning model.
org.apache.flink.ml - 程序包 org.apache.flink.ml
org.apache.flink.ml.classification.knn - 程序包 org.apache.flink.ml.classification.knn
org.apache.flink.ml.classification.linearsvc - 程序包 org.apache.flink.ml.classification.linearsvc
org.apache.flink.ml.classification.logisticregression - 程序包 org.apache.flink.ml.classification.logisticregression
org.apache.flink.ml.classification.naivebayes - 程序包 org.apache.flink.ml.classification.naivebayes
org.apache.flink.ml.clustering.agglomerativeclustering - 程序包 org.apache.flink.ml.clustering.agglomerativeclustering
org.apache.flink.ml.clustering.kmeans - 程序包 org.apache.flink.ml.clustering.kmeans
org.apache.flink.ml.common.lossfunc - 程序包 org.apache.flink.ml.common.lossfunc
org.apache.flink.ml.common.optimizer - 程序包 org.apache.flink.ml.common.optimizer
org.apache.flink.ml.common.param - 程序包 org.apache.flink.ml.common.param
org.apache.flink.ml.common.typeinfo - 程序包 org.apache.flink.ml.common.typeinfo
org.apache.flink.ml.common.util - 程序包 org.apache.flink.ml.common.util
org.apache.flink.ml.evaluation.binaryclassification - 程序包 org.apache.flink.ml.evaluation.binaryclassification
org.apache.flink.ml.feature.binarizer - 程序包 org.apache.flink.ml.feature.binarizer
org.apache.flink.ml.feature.bucketizer - 程序包 org.apache.flink.ml.feature.bucketizer
org.apache.flink.ml.feature.countvectorizer - 程序包 org.apache.flink.ml.feature.countvectorizer
org.apache.flink.ml.feature.dct - 程序包 org.apache.flink.ml.feature.dct
org.apache.flink.ml.feature.elementwiseproduct - 程序包 org.apache.flink.ml.feature.elementwiseproduct
org.apache.flink.ml.feature.featurehasher - 程序包 org.apache.flink.ml.feature.featurehasher
org.apache.flink.ml.feature.hashingtf - 程序包 org.apache.flink.ml.feature.hashingtf
org.apache.flink.ml.feature.idf - 程序包 org.apache.flink.ml.feature.idf
org.apache.flink.ml.feature.imputer - 程序包 org.apache.flink.ml.feature.imputer
org.apache.flink.ml.feature.interaction - 程序包 org.apache.flink.ml.feature.interaction
org.apache.flink.ml.feature.kbinsdiscretizer - 程序包 org.apache.flink.ml.feature.kbinsdiscretizer
org.apache.flink.ml.feature.lsh - 程序包 org.apache.flink.ml.feature.lsh
org.apache.flink.ml.feature.maxabsscaler - 程序包 org.apache.flink.ml.feature.maxabsscaler
org.apache.flink.ml.feature.minmaxscaler - 程序包 org.apache.flink.ml.feature.minmaxscaler
org.apache.flink.ml.feature.ngram - 程序包 org.apache.flink.ml.feature.ngram
org.apache.flink.ml.feature.normalizer - 程序包 org.apache.flink.ml.feature.normalizer
org.apache.flink.ml.feature.onehotencoder - 程序包 org.apache.flink.ml.feature.onehotencoder
org.apache.flink.ml.feature.polynomialexpansion - 程序包 org.apache.flink.ml.feature.polynomialexpansion
org.apache.flink.ml.feature.randomsplitter - 程序包 org.apache.flink.ml.feature.randomsplitter
org.apache.flink.ml.feature.regextokenizer - 程序包 org.apache.flink.ml.feature.regextokenizer
org.apache.flink.ml.feature.robustscaler - 程序包 org.apache.flink.ml.feature.robustscaler
org.apache.flink.ml.feature.sqltransformer - 程序包 org.apache.flink.ml.feature.sqltransformer
org.apache.flink.ml.feature.standardscaler - 程序包 org.apache.flink.ml.feature.standardscaler
org.apache.flink.ml.feature.stopwordsremover - 程序包 org.apache.flink.ml.feature.stopwordsremover
org.apache.flink.ml.feature.stringindexer - 程序包 org.apache.flink.ml.feature.stringindexer
org.apache.flink.ml.feature.tokenizer - 程序包 org.apache.flink.ml.feature.tokenizer
org.apache.flink.ml.feature.univariatefeatureselector - 程序包 org.apache.flink.ml.feature.univariatefeatureselector
org.apache.flink.ml.feature.variancethresholdselector - 程序包 org.apache.flink.ml.feature.variancethresholdselector
org.apache.flink.ml.feature.vectorassembler - 程序包 org.apache.flink.ml.feature.vectorassembler
org.apache.flink.ml.feature.vectorindexer - 程序包 org.apache.flink.ml.feature.vectorindexer
org.apache.flink.ml.feature.vectorslicer - 程序包 org.apache.flink.ml.feature.vectorslicer
org.apache.flink.ml.recommendation.swing - 程序包 org.apache.flink.ml.recommendation.swing
org.apache.flink.ml.regression.linearregression - 程序包 org.apache.flink.ml.regression.linearregression
org.apache.flink.ml.stats.anovatest - 程序包 org.apache.flink.ml.stats.anovatest
org.apache.flink.ml.stats.chisqtest - 程序包 org.apache.flink.ml.stats.chisqtest
org.apache.flink.ml.stats.fvaluetest - 程序包 org.apache.flink.ml.stats.fvaluetest

P

P - 接口中的静态变量org.apache.flink.ml.feature.normalizer.NormalizerParams
packedFeatures - 类中的变量org.apache.flink.ml.classification.knn.KnnModelData
PATTERN - 接口中的静态变量org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
PERCENTILE - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
piArray - 类中的变量org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData: Log of class priors, whose dimension is C (number of classes).
PolynomialExpansion - org.apache.flink.ml.feature.polynomialexpansion中的类: A Transformer that expands the input vectors in polynomial space.
PolynomialExpansion() - 类的构造器org.apache.flink.ml.feature.polynomialexpansion.PolynomialExpansion
PolynomialExpansionParams<T> - org.apache.flink.ml.feature.polynomialexpansion中的接口: Params of PolynomialExpansion.
PriorityQueueSerializer<T> - org.apache.flink.ml.common.typeinfo中的类: TypeSerializer for PriorityQueue.
PriorityQueueSerializer(Comparator<? super T>, TypeSerializer<T>) - 类的构造器org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
PriorityQueueTypeInfo<T> - org.apache.flink.ml.common.typeinfo中的类: TypeInformation for PriorityQueue.
PriorityQueueTypeInfo(Comparator<? super T>, TypeInformation<T>) - 类的构造器org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
processElement(StreamRecord<DenseVector>) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler.MinMaxReduceFunctionOperator

Q

QUANTILE - 接口中的静态变量org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
QuantileSummary - org.apache.flink.ml.common.util中的类: Helper class to compute an approximate quantile summary.
QuantileSummary() - 类的构造器org.apache.flink.ml.common.util.QuantileSummary: Empty QuantileSummary Constructor.
QuantileSummary(double) - 类的构造器org.apache.flink.ml.common.util.QuantileSummary: QuantileSummary Constructor.
QuantileSummary(double, int) - 类的构造器org.apache.flink.ml.common.util.QuantileSummary: QuantileSummary Constructor.
QuantileSummary(double, int, List<QuantileSummary.StatsTuple>, long, boolean) - 类的构造器org.apache.flink.ml.common.util.QuantileSummary: QuantileSummary Constructor.
QuantileSummary.StatsTuple - org.apache.flink.ml.common.util中的类: Wrapper class to hold all statistics from the Greenwald-Khanna paper.
QuantileSummaryTypeInfoFactory - org.apache.flink.ml.common.typeinfo中的类: Used by TypeExtractor to create a TypeInformation for implementations of QuantileSummary.
QuantileSummaryTypeInfoFactory() - 类的构造器org.apache.flink.ml.common.typeinfo.QuantileSummaryTypeInfoFactory
query(double) - 类中的方法org.apache.flink.ml.common.util.QuantileSummary: Runs a query for a given percentile.
query(double[]) - 类中的方法org.apache.flink.ml.common.util.QuantileSummary: Runs a query for a given sequence of percentiles.

R

randCoefficientA - 类中的变量org.apache.flink.ml.feature.lsh.MinHashLSHModelData
randCoefficientB - 类中的变量org.apache.flink.ml.feature.lsh.MinHashLSHModelData
RandomSplitter - org.apache.flink.ml.feature.randomsplitter中的类: An AlgoOperator which splits a Table into N Tables according to the given weights.
RandomSplitter() - 类的构造器org.apache.flink.ml.feature.randomsplitter.RandomSplitter
RandomSplitterParams<T> - org.apache.flink.ml.feature.randomsplitter中的接口: Params of RandomSplitter.
ranges - 类中的变量org.apache.flink.ml.feature.robustscaler.RobustScalerModelData
RegexTokenizer - org.apache.flink.ml.feature.regextokenizer中的类: A Transformer which converts the input string to lowercase and then splits it by white spaces based on regex.
RegexTokenizer() - 类的构造器org.apache.flink.ml.feature.regextokenizer.RegexTokenizer
RegexTokenizer.RegexTokenizerUdf - org.apache.flink.ml.feature.regextokenizer中的类: The main logic of $RegexTokenizer, which converts the input string to an array of tokens.
RegexTokenizerParams<T> - org.apache.flink.ml.feature.regextokenizer中的接口: Params for RegexTokenizer.
RegexTokenizerUdf() - 类的构造器org.apache.flink.ml.feature.regextokenizer.RegexTokenizer.RegexTokenizerUdf
RemoveStopWordsFunction(Set<String>, Locale, boolean) - 类的构造器org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover.RemoveStopWordsFunction
RobustScaler - org.apache.flink.ml.feature.robustscaler中的类: An Estimator which scales features using statistics that are robust to outliers.
RobustScaler() - 类的构造器org.apache.flink.ml.feature.robustscaler.RobustScaler
RobustScalerModel - org.apache.flink.ml.feature.robustscaler中的类: A Model which transforms data using the model data computed by RobustScaler.
RobustScalerModel() - 类的构造器org.apache.flink.ml.feature.robustscaler.RobustScalerModel
RobustScalerModelData - org.apache.flink.ml.feature.robustscaler中的类: Model data of RobustScalerModel.
RobustScalerModelData() - 类的构造器org.apache.flink.ml.feature.robustscaler.RobustScalerModelData
RobustScalerModelData(DenseVector, DenseVector) - 类的构造器org.apache.flink.ml.feature.robustscaler.RobustScalerModelData
RobustScalerModelData.ModelDataDecoder - org.apache.flink.ml.feature.robustscaler中的类: Data decoder for the RobustScalerModel model data.
RobustScalerModelData.ModelDataEncoder - org.apache.flink.ml.feature.robustscaler中的类: Data encoder for the RobustScalerModel model data.
RobustScalerModelParams<T> - org.apache.flink.ml.feature.robustscaler中的接口: Params for RobustScalerModel.
RobustScalerParams<T> - org.apache.flink.ml.feature.robustscaler中的接口: Params for RobustScaler.

S

save(String) - 类中的方法org.apache.flink.ml.classification.knn.Knn
save(String) - 类中的方法org.apache.flink.ml.classification.knn.KnnModel
save(String) - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVC
save(String) - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModel
save(String) - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegression
save(String) - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModel
save(String) - 类中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegression
save(String) - 类中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModel
save(String) - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayes
save(String) - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModel
save(String) - 类中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClustering
save(String) - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeans
save(String) - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeansModel
save(String) - 类中的方法org.apache.flink.ml.clustering.kmeans.OnlineKMeans: Saves the metadata AND bounded model data table (if exists) to the given path.
save(String) - 类中的方法org.apache.flink.ml.clustering.kmeans.OnlineKMeansModel: Saves the metadata to the given path.
save(String) - 类中的方法org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator
save(String) - 类中的方法org.apache.flink.ml.feature.binarizer.Binarizer
save(String) - 类中的方法org.apache.flink.ml.feature.bucketizer.Bucketizer
save(String) - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizer
save(String) - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModel
save(String) - 类中的方法org.apache.flink.ml.feature.dct.DCT
save(String) - 类中的方法org.apache.flink.ml.feature.elementwiseproduct.ElementwiseProduct
save(String) - 类中的方法org.apache.flink.ml.feature.featurehasher.FeatureHasher
save(String) - 类中的方法org.apache.flink.ml.feature.hashingtf.HashingTF
save(String) - 类中的方法org.apache.flink.ml.feature.idf.IDF
save(String) - 类中的方法org.apache.flink.ml.feature.idf.IDFModel
save(String) - 类中的方法org.apache.flink.ml.feature.imputer.Imputer
save(String) - 类中的方法org.apache.flink.ml.feature.imputer.ImputerModel
save(String) - 类中的方法org.apache.flink.ml.feature.interaction.Interaction
save(String) - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizer
save(String) - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModel
save(String) - 类中的方法org.apache.flink.ml.feature.lsh.MinHashLSHModel
save(String) - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScaler
save(String) - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModel
save(String) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler
save(String) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModel
save(String) - 类中的方法org.apache.flink.ml.feature.ngram.NGram
save(String) - 类中的方法org.apache.flink.ml.feature.normalizer.Normalizer
save(String) - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoder
save(String) - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModel
save(String) - 类中的方法org.apache.flink.ml.feature.polynomialexpansion.PolynomialExpansion
save(String) - 类中的方法org.apache.flink.ml.feature.randomsplitter.RandomSplitter
save(String) - 类中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizer
save(String) - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScaler
save(String) - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModel
save(String) - 类中的方法org.apache.flink.ml.feature.sqltransformer.SQLTransformer
save(String) - 类中的方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScaler
save(String) - 类中的方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScalerModel
save(String) - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScaler
save(String) - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerModel
save(String) - 类中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover
save(String) - 类中的方法org.apache.flink.ml.feature.stringindexer.IndexToStringModel
save(String) - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexer
save(String) - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerModel
save(String) - 类中的方法org.apache.flink.ml.feature.tokenizer.Tokenizer
save(String) - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelector
save(String) - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModel
save(String) - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelector
save(String) - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModel
save(String) - 类中的方法org.apache.flink.ml.feature.vectorassembler.VectorAssembler
save(String) - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexer
save(String) - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModel
save(String) - 类中的方法org.apache.flink.ml.feature.vectorslicer.VectorSlicer
save(String) - 类中的方法org.apache.flink.ml.recommendation.swing.Swing
save(String) - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegression
save(String) - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegressionModel
save(String) - 类中的方法org.apache.flink.ml.stats.anovatest.ANOVATest
save(String) - 类中的方法org.apache.flink.ml.stats.chisqtest.ChiSqTest
save(String) - 类中的方法org.apache.flink.ml.stats.fvaluetest.FValueTest
SCALING_VEC - 接口中的静态变量org.apache.flink.ml.feature.elementwiseproduct.ElementwiseProductParams
selectByIndices(Vector, int[]) - 类中的静态方法org.apache.flink.ml.common.util.VectorUtils: Selects a subset of the vector base on the indices.
SELECTION_MODE - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams: Supported options of the feature selection mode.
SELECTION_THRESHOLD - 接口中的静态变量org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
selectRandomCentroids(DataStream<DenseVector>, int, long) - 类中的静态方法org.apache.flink.ml.clustering.kmeans.KMeans
serialize(PriorityQueue<T>, DataOutputView) - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
setAlpha(Double) - 接口中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionParams
setAlpha1(Integer) - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
setAlpha2(Integer) - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
setBeta(Double) - 接口中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionParams
setBeta(Double) - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
setBinary(boolean) - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelParams
setBinary(boolean) - 接口中的方法org.apache.flink.ml.feature.hashingtf.HashingTFParams
setCaseSensitive(boolean) - 接口中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemoverParams
setComputeFullTree(Boolean) - 接口中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
setDegree(Integer) - 接口中的方法org.apache.flink.ml.feature.polynomialexpansion.PolynomialExpansionParams
setDistanceThreshold(Double) - 接口中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
setDropLast(boolean) - 接口中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderParams
setFeatureType(String) - 接口中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
setGaps(boolean) - 接口中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
setIndices(Integer...) - 接口中的方法org.apache.flink.ml.feature.vectorslicer.VectorSlicerParams
setInitialModelData(Table) - 类中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegression: Sets the initial model data of the online training process with the provided model data table.
setInitialModelData(Table) - 类中的方法org.apache.flink.ml.clustering.kmeans.OnlineKMeans: Sets the initial model data of the online training process with the provided model data table.
setInitMode(String) - 接口中的方法org.apache.flink.ml.clustering.kmeans.KMeansParams
setInputSizes(Integer...) - 接口中的方法org.apache.flink.ml.feature.vectorassembler.VectorAssemblerParams
setInverse(boolean) - 接口中的方法org.apache.flink.ml.feature.dct.DCTParams
setItemCol(String) - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
setK(int) - 接口中的方法org.apache.flink.ml.clustering.kmeans.KMeansModelParams
setK(Integer) - 接口中的方法org.apache.flink.ml.classification.knn.KnnModelParams
setK(Integer) - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
setLabelType(String) - 接口中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
setLinkage(String) - 接口中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
setLocale(String) - 接口中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemoverParams
setLower(Double) - 接口中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerParams
setMax(Double) - 接口中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerParams
setMaxCategories(int) - 接口中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerParams
setMaxDF(double) - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerParams
setMaxIndexNum(int) - 接口中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerParams
setMaxUserBehavior(Integer) - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
setMaxUserNumPerItem(Integer) - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
setMetricsNames(String...) - 接口中的方法org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluatorParams
setMin(Double) - 接口中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerParams
setMinDF(double) - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerParams
setMinDocFreq(Integer) - 接口中的方法org.apache.flink.ml.feature.idf.IDFParams
setMinTF(double) - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelParams
setMinTokenLength(int) - 接口中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
setMinUserBehavior(Integer) - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
setMissingValue(double) - 接口中的方法org.apache.flink.ml.feature.imputer.ImputerModelParams
setModelData(Table...) - 类中的方法org.apache.flink.ml.classification.knn.KnnModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeansModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.clustering.kmeans.OnlineKMeansModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.idf.IDFModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.imputer.ImputerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScalerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.stringindexer.IndexToStringModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModel
setModelData(Table...) - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegressionModel
setModelType(String) - 接口中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModelParams
setModelVersionCol(String) - 接口中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModelParams
setN(int) - 接口中的方法org.apache.flink.ml.feature.ngram.NGramParams
setNumBins(int) - 接口中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
setNumClusters(Integer) - 接口中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClusteringParams
setNumHashFunctionsPerTable(Integer) - 接口中的方法org.apache.flink.ml.feature.lsh.LSHParams
setNumHashTables(Integer) - 接口中的方法org.apache.flink.ml.feature.lsh.LSHParams
setP(Double) - 接口中的方法org.apache.flink.ml.feature.normalizer.NormalizerParams
setPattern(String) - 接口中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
setScalingVec(Vector) - 接口中的方法org.apache.flink.ml.feature.elementwiseproduct.ElementwiseProductParams
setSelectionMode(String) - 接口中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
setSelectionThreshold(double) - 接口中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorParams
setSmoothing(Double) - 接口中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesParams
setSplitsArray(Double[][]) - 接口中的方法org.apache.flink.ml.feature.bucketizer.BucketizerParams
setStatement(String) - 接口中的方法org.apache.flink.ml.feature.sqltransformer.SQLTransformerParams
setStopWords(String[]) - 接口中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemoverParams
setStrategy(String) - 接口中的方法org.apache.flink.ml.feature.imputer.ImputerParams
setStrategy(String) - 接口中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
setStringOrderType(String) - 接口中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerParams
setSubSamples(Integer) - 接口中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
setThreshold(Double) - 接口中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModelParams
setThresholds(Double...) - 接口中的方法org.apache.flink.ml.feature.binarizer.BinarizerParams
setToLowercase(boolean) - 接口中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
setUpper(Double) - 接口中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerParams
setUserCol(String) - 接口中的方法org.apache.flink.ml.recommendation.swing.SwingParams
setVarianceThreshold(double) - 接口中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorParams
setVocabularySize(int) - 接口中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerParams
setWeights(Double...) - 接口中的方法org.apache.flink.ml.feature.randomsplitter.RandomSplitterParams
setWindows(Windows) - 接口中的方法org.apache.flink.ml.common.param.HasWindows
setWithCentering(boolean) - 接口中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModelParams
setWithMean(boolean) - 接口中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerParams
setWithScaling(boolean) - 接口中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModelParams
setWithStd(boolean) - 接口中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerParams
SGD - org.apache.flink.ml.common.optimizer中的类: Stochastic Gradient Descent (SGD) is the mostly wide-used optimizer for optimizing machine learning models.
SGD(int, double, int, double, double, double) - 类的构造器org.apache.flink.ml.common.optimizer.SGD
shallowCopy() - 类中的方法org.apache.flink.ml.common.util.QuantileSummary.StatsTuple
sizesValidator() - 接口中的静态方法org.apache.flink.ml.feature.vectorassembler.VectorAssemblerParams
SMOOTHING - 接口中的静态变量org.apache.flink.ml.classification.naivebayes.NaiveBayesParams
snapshotConfiguration() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueSerializer
snapshotState(StateSnapshotContext) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScaler.MinMaxReduceFunctionOperator
SPLITS_ARRAY - 接口中的静态变量org.apache.flink.ml.feature.bucketizer.BucketizerParams: The array of split points for mapping continuous features into buckets for multiple columns.
SplitsArrayValidator() - 类的构造器org.apache.flink.ml.feature.bucketizer.BucketizerParams.SplitsArrayValidator
SQLStatementValidator() - 类的构造器org.apache.flink.ml.feature.sqltransformer.SQLTransformerParams.SQLStatementValidator
SQLTransformer - org.apache.flink.ml.feature.sqltransformer中的类: SQLTransformer implements the transformations that are defined by SQL statement.
SQLTransformer() - 类的构造器org.apache.flink.ml.feature.sqltransformer.SQLTransformer
SQLTransformerParams<T> - org.apache.flink.ml.feature.sqltransformer中的接口: Params for SQLTransformer.
SQLTransformerParams.SQLStatementValidator - org.apache.flink.ml.feature.sqltransformer中的类: Param validator for SQL statements.
StandardScaler - org.apache.flink.ml.feature.standardscaler中的类: An Estimator which implements the standard scaling algorithm.
StandardScaler() - 类的构造器org.apache.flink.ml.feature.standardscaler.StandardScaler
StandardScalerModel - org.apache.flink.ml.feature.standardscaler中的类: A Model which transforms data using the model data computed by StandardScaler.
StandardScalerModel() - 类的构造器org.apache.flink.ml.feature.standardscaler.StandardScalerModel
StandardScalerModelData - org.apache.flink.ml.feature.standardscaler中的类: Model data of StandardScalerModel.
StandardScalerModelData() - 类的构造器org.apache.flink.ml.feature.standardscaler.StandardScalerModelData
StandardScalerModelData(DenseVector, DenseVector) - 类的构造器org.apache.flink.ml.feature.standardscaler.StandardScalerModelData
StandardScalerModelData(DenseVector, DenseVector, long, long) - 类的构造器org.apache.flink.ml.feature.standardscaler.StandardScalerModelData
StandardScalerModelData.ModelDataDecoder - org.apache.flink.ml.feature.standardscaler中的类: Data decoder for the StandardScalerModel model data.
StandardScalerModelData.ModelDataEncoder - org.apache.flink.ml.feature.standardscaler中的类: Data encoder for the StandardScalerModel model data.
StandardScalerParams<T> - org.apache.flink.ml.feature.standardscaler中的接口: Params for StandardScaler.
STATEMENT - 接口中的静态变量org.apache.flink.ml.feature.sqltransformer.SQLTransformerParams
StatsTuple() - 类的构造器org.apache.flink.ml.common.util.QuantileSummary.StatsTuple
StatsTuple(double, long, long) - 类的构造器org.apache.flink.ml.common.util.QuantileSummary.StatsTuple
std - 类中的变量org.apache.flink.ml.feature.standardscaler.StandardScalerModelData: Standard deviation of each dimension.
STOP_WORDS - 接口中的静态变量org.apache.flink.ml.feature.stopwordsremover.StopWordsRemoverParams
StopWordsRemover - org.apache.flink.ml.feature.stopwordsremover中的类: A feature transformer that filters out stop words from input.
StopWordsRemover() - 类的构造器org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover
StopWordsRemover.RemoveStopWordsFunction - org.apache.flink.ml.feature.stopwordsremover中的类: A Scalar Function that removes stop words from input string array.
StopWordsRemoverParams<T> - org.apache.flink.ml.feature.stopwordsremover中的接口: Params of StopWordsRemover.
STRATEGY - 接口中的静态变量org.apache.flink.ml.feature.imputer.ImputerParams: Supported options of the imputation strategy.
STRATEGY - 接口中的静态变量org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams: Supported options to define the widths of the bins are listed as follows.
STRING_ORDER_TYPE - 接口中的静态变量org.apache.flink.ml.feature.stringindexer.StringIndexerParams: Supported options to decide the order of strings in each column are listed as follows.
stringArrays - 类中的变量org.apache.flink.ml.feature.stringindexer.StringIndexerModelData: Ordered strings of each input column.
StringIndexer - org.apache.flink.ml.feature.stringindexer中的类: An Estimator which implements the string indexing algorithm.
StringIndexer() - 类的构造器org.apache.flink.ml.feature.stringindexer.StringIndexer
StringIndexerModel - org.apache.flink.ml.feature.stringindexer中的类: A Model which transforms input string/numeric column(s) to double column(s) using the model data computed by StringIndexer.
StringIndexerModel() - 类的构造器org.apache.flink.ml.feature.stringindexer.StringIndexerModel
StringIndexerModelData - org.apache.flink.ml.feature.stringindexer中的类: Model data of StringIndexerModel and IndexToStringModel.
StringIndexerModelData() - 类的构造器org.apache.flink.ml.feature.stringindexer.StringIndexerModelData
StringIndexerModelData(String[][]) - 类的构造器org.apache.flink.ml.feature.stringindexer.StringIndexerModelData
StringIndexerModelData.ModelDataDecoder - org.apache.flink.ml.feature.stringindexer中的类: Data decoder for StringIndexerModel and IndexToStringModel.
StringIndexerModelData.ModelDataEncoder - org.apache.flink.ml.feature.stringindexer中的类: Data encoder for StringIndexerModel and IndexToStringModel.
StringIndexerModelParams<T> - org.apache.flink.ml.feature.stringindexer中的接口: Params of StringIndexerModel.
StringIndexerParams<T> - org.apache.flink.ml.feature.stringindexer中的接口: Params of StringIndexer.
SUB_SAMPLES - 接口中的静态变量org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
surrogates - 类中的变量org.apache.flink.ml.feature.imputer.ImputerModelData
Swing - org.apache.flink.ml.recommendation.swing中的类: An AlgoOperator which implements the Swing algorithm.
Swing() - 类的构造器org.apache.flink.ml.recommendation.swing.Swing
SwingParams<T> - org.apache.flink.ml.recommendation.swing中的接口: Params for Swing.

T

taskId - 类中的变量org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator.BinarySummary
theta - 类中的变量org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData: Log of class conditional probabilities, whose dimension is C (number of classes) by D (number of features).
THRESHOLD - 接口中的静态变量org.apache.flink.ml.classification.linearsvc.LinearSVCModelParams: Param for threshold in linear support vector classifier.
THRESHOLDS - 接口中的静态变量org.apache.flink.ml.feature.binarizer.BinarizerParams
timestamp - 类中的变量org.apache.flink.ml.feature.standardscaler.StandardScalerModelData: Model timestamp.
TO_LOWERCASE - 接口中的静态变量org.apache.flink.ml.feature.regextokenizer.RegexTokenizerParams
Tokenizer - org.apache.flink.ml.feature.tokenizer中的类: A Transformer which converts the input string to lowercase and then splits it by white spaces.
Tokenizer() - 类的构造器org.apache.flink.ml.feature.tokenizer.Tokenizer
Tokenizer.TokenizerUdf - org.apache.flink.ml.feature.tokenizer中的类: The main logic of Tokenizer, which converts the input string to an array of tokens.
TokenizerParams<T> - org.apache.flink.ml.feature.tokenizer中的接口: Params of Tokenizer.
TokenizerUdf() - 类的构造器org.apache.flink.ml.feature.tokenizer.Tokenizer.TokenizerUdf
toString() - 类中的方法org.apache.flink.ml.common.typeinfo.PriorityQueueTypeInfo
transform(Table...) - 类中的方法org.apache.flink.ml.classification.knn.KnnModel
transform(Table...) - 类中的方法org.apache.flink.ml.classification.linearsvc.LinearSVCModel
transform(Table...) - 类中的方法org.apache.flink.ml.classification.logisticregression.LogisticRegressionModel
transform(Table...) - 类中的方法org.apache.flink.ml.classification.logisticregression.OnlineLogisticRegressionModel
transform(Table...) - 类中的方法org.apache.flink.ml.classification.naivebayes.NaiveBayesModel
transform(Table...) - 类中的方法org.apache.flink.ml.clustering.agglomerativeclustering.AgglomerativeClustering
transform(Table...) - 类中的方法org.apache.flink.ml.clustering.kmeans.KMeansModel
transform(Table...) - 类中的方法org.apache.flink.ml.clustering.kmeans.OnlineKMeansModel
transform(Table...) - 类中的方法org.apache.flink.ml.evaluation.binaryclassification.BinaryClassificationEvaluator
transform(Table...) - 类中的方法org.apache.flink.ml.feature.binarizer.Binarizer
transform(Table...) - 类中的方法org.apache.flink.ml.feature.bucketizer.Bucketizer
transform(Table...) - 类中的方法org.apache.flink.ml.feature.countvectorizer.CountVectorizerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.dct.DCT
transform(Table...) - 类中的方法org.apache.flink.ml.feature.elementwiseproduct.ElementwiseProduct
transform(Table...) - 类中的方法org.apache.flink.ml.feature.featurehasher.FeatureHasher
transform(Table...) - 类中的方法org.apache.flink.ml.feature.hashingtf.HashingTF
transform(Table...) - 类中的方法org.apache.flink.ml.feature.idf.IDFModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.imputer.ImputerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.interaction.Interaction
transform(Table...) - 类中的方法org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.maxabsscaler.MaxAbsScalerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.minmaxscaler.MinMaxScalerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.ngram.NGram
transform(Table...) - 类中的方法org.apache.flink.ml.feature.normalizer.Normalizer
transform(Table...) - 类中的方法org.apache.flink.ml.feature.onehotencoder.OneHotEncoderModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.polynomialexpansion.PolynomialExpansion
transform(Table...) - 类中的方法org.apache.flink.ml.feature.randomsplitter.RandomSplitter
transform(Table...) - 类中的方法org.apache.flink.ml.feature.regextokenizer.RegexTokenizer
transform(Table...) - 类中的方法org.apache.flink.ml.feature.robustscaler.RobustScalerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.sqltransformer.SQLTransformer
transform(Table...) - 类中的方法org.apache.flink.ml.feature.standardscaler.OnlineStandardScalerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.standardscaler.StandardScalerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.stopwordsremover.StopWordsRemover
transform(Table...) - 类中的方法org.apache.flink.ml.feature.stringindexer.IndexToStringModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.stringindexer.StringIndexerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.tokenizer.Tokenizer
transform(Table...) - 类中的方法org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.vectorassembler.VectorAssembler
transform(Table...) - 类中的方法org.apache.flink.ml.feature.vectorindexer.VectorIndexerModel
transform(Table...) - 类中的方法org.apache.flink.ml.feature.vectorslicer.VectorSlicer
transform(Table...) - 类中的方法org.apache.flink.ml.recommendation.swing.Swing
transform(Table...) - 类中的方法org.apache.flink.ml.regression.linearregression.LinearRegressionModel
transform(Table...) - 类中的方法org.apache.flink.ml.stats.anovatest.ANOVATest
transform(Table...) - 类中的方法org.apache.flink.ml.stats.chisqtest.ChiSqTest
transform(Table...) - 类中的方法org.apache.flink.ml.stats.fvaluetest.FValueTest
TYPE_INFO - 类中的静态变量org.apache.flink.ml.classification.naivebayes.NaiveBayesModelData
TYPE_INFO - 类中的静态变量org.apache.flink.ml.feature.imputer.ImputerModelData
TYPE_INFO - 类中的静态变量org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData

U

UNIFORM - 接口中的静态变量org.apache.flink.ml.feature.kbinsdiscretizer.KBinsDiscretizerParams
UnivariateFeatureSelector - org.apache.flink.ml.feature.univariatefeatureselector中的类: An Estimator which selects features based on univariate statistical tests against labels.
UnivariateFeatureSelector() - 类的构造器org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelector
UnivariateFeatureSelectorModel - org.apache.flink.ml.feature.univariatefeatureselector中的类: A Model which transforms data using the model data computed by UnivariateFeatureSelector.
UnivariateFeatureSelectorModel() - 类的构造器org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModel
UnivariateFeatureSelectorModelData - org.apache.flink.ml.feature.univariatefeatureselector中的类: Model data of UnivariateFeatureSelectorModel.
UnivariateFeatureSelectorModelData() - 类的构造器org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModelData
UnivariateFeatureSelectorModelData(int[]) - 类的构造器org.apache.flink.ml.feature.univariatefeatureselector.UnivariateFeatureSelectorModelData
UnivariateFeatureSelectorModelData.ModelDataDecoder - org.apache.flink.ml.feature.univariatefeatureselector中的类: Decoder for UnivariateFeatureSelectorModelData.
UnivariateFeatureSelectorModelData.ModelDataEncoder - org.apache.flink.ml.feature.univariatefeatureselector中的类: Encoder for UnivariateFeatureSelectorModelData.
UnivariateFeatureSelectorModelParams<T> - org.apache.flink.ml.feature.univariatefeatureselector中的接口: Params for UnivariateFeatureSelectorModel.
UnivariateFeatureSelectorParams<T> - org.apache.flink.ml.feature.univariatefeatureselector中的接口: Params for UnivariateFeatureSelector.
UPPER - 接口中的静态变量org.apache.flink.ml.feature.robustscaler.RobustScalerParams
USER_COL - 接口中的静态变量org.apache.flink.ml.recommendation.swing.SwingParams

V

validate(Double[][]) - 类中的方法org.apache.flink.ml.feature.bucketizer.BucketizerParams.SplitsArrayValidator
validate(String) - 类中的方法org.apache.flink.ml.feature.sqltransformer.SQLTransformerParams.SQLStatementValidator
value - 类中的变量org.apache.flink.ml.common.util.QuantileSummary.StatsTuple
VARIANCE_THRESHOLD - 接口中的静态变量org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorParams
VarianceThresholdSelector - org.apache.flink.ml.feature.variancethresholdselector中的类: An Estimator which implements the VarianceThresholdSelector algorithm.
VarianceThresholdSelector() - 类的构造器org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelector
VarianceThresholdSelectorModel - org.apache.flink.ml.feature.variancethresholdselector中的类: A Model which removes low-variance data using the model data computed by VarianceThresholdSelector.
VarianceThresholdSelectorModel() - 类的构造器org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModel
VarianceThresholdSelectorModelData - org.apache.flink.ml.feature.variancethresholdselector中的类: Model data of VarianceThresholdSelectorModel.
VarianceThresholdSelectorModelData() - 类的构造器org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData
VarianceThresholdSelectorModelData(int, int[]) - 类的构造器org.apache.flink.ml.feature.variancethresholdselector.VarianceThresholdSelectorModelData
VarianceThresholdSelectorModelData.ModelDataDecoder - org.apache.flink.ml.feature.variancethresholdselector中的类: Decoder for VarianceThresholdSelectorModelData.
VarianceThresholdSelectorModelData.ModelDataEncoder - org.apache.flink.ml.feature.variancethresholdselector中的类: Encoder for VarianceThresholdSelectorModelData.
VarianceThresholdSelectorModelParams<T> - org.apache.flink.ml.feature.variancethresholdselector中的接口: Params for VarianceThresholdSelectorModel.
VarianceThresholdSelectorParams<T> - org.apache.flink.ml.feature.variancethresholdselector中的接口: Params of VarianceThresholdSelectorModel.
VectorAssembler - org.apache.flink.ml.feature.vectorassembler中的类: A Transformer which combines a given list of input columns into a vector column.
VectorAssembler() - 类的构造器org.apache.flink.ml.feature.vectorassembler.VectorAssembler
VectorAssemblerParams<T> - org.apache.flink.ml.feature.vectorassembler中的接口: Params of VectorAssembler.
VectorIndexer - org.apache.flink.ml.feature.vectorindexer中的类: An Estimator which implements the vector indexing algorithm.
VectorIndexer() - 类的构造器org.apache.flink.ml.feature.vectorindexer.VectorIndexer
VectorIndexerModel - org.apache.flink.ml.feature.vectorindexer中的类: A Model which encodes input vector to an output vector using the model data computed by VectorIndexer.
VectorIndexerModel() - 类的构造器org.apache.flink.ml.feature.vectorindexer.VectorIndexerModel
VectorIndexerModelData - org.apache.flink.ml.feature.vectorindexer中的类: Model data of VectorIndexerModel.
VectorIndexerModelData() - 类的构造器org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData
VectorIndexerModelData(Map<Integer, Map<Double, Integer>>) - 类的构造器org.apache.flink.ml.feature.vectorindexer.VectorIndexerModelData
VectorIndexerModelData.ModelDataDecoder - org.apache.flink.ml.feature.vectorindexer中的类: Data decoder for VectorIndexerModel.
VectorIndexerModelData.ModelDataEncoder - org.apache.flink.ml.feature.vectorindexer中的类: Data encoder for VectorIndexerModel.
VectorIndexerModelParams<T> - org.apache.flink.ml.feature.vectorindexer中的接口: Params for VectorIndexerModel.
VectorIndexerParams<T> - org.apache.flink.ml.feature.vectorindexer中的接口: Params of VectorIndexer.
VectorSlicer - org.apache.flink.ml.feature.vectorslicer中的类: A Transformer that transforms a vector to a new feature, which is a sub-array of the original feature.
VectorSlicer() - 类的构造器org.apache.flink.ml.feature.vectorslicer.VectorSlicer
VectorSlicerParams<T> - org.apache.flink.ml.feature.vectorslicer中的接口: Params of VectorSlicer.
vectorToArray(Object...) - 类中的静态方法org.apache.flink.ml.Functions: Converts a column of Vectors into a column of double arrays.
VectorToArrayFunction() - 类的构造器org.apache.flink.ml.Functions.VectorToArrayFunction
VectorUtils - org.apache.flink.ml.common.util中的类: Provides utility functions for Vector.
VectorUtils() - 类的构造器org.apache.flink.ml.common.util.VectorUtils
version - 类中的变量org.apache.flink.ml.feature.standardscaler.StandardScalerModelData: Model version.
vocabulary - 类中的变量org.apache.flink.ml.feature.countvectorizer.CountVectorizerModelData: The array over terms, only the terms in the vocabulary will be counted.
VOCABULARY_SIZE - 接口中的静态变量org.apache.flink.ml.feature.countvectorizer.CountVectorizerParams

W

weights - 类中的变量org.apache.flink.ml.clustering.kmeans.KMeansModelData: The weight of the centroids.
WEIGHTS - 接口中的静态变量org.apache.flink.ml.feature.randomsplitter.RandomSplitterParams: Weights should be a non-empty array with all elements greater than zero.
weightsValidator() - 接口中的静态方法org.apache.flink.ml.feature.randomsplitter.RandomSplitterParams
WINDOWS - 接口中的静态变量org.apache.flink.ml.common.param.HasWindows
WITH_CENTERING - 接口中的静态变量org.apache.flink.ml.feature.robustscaler.RobustScalerModelParams
WITH_MEAN - 接口中的静态变量org.apache.flink.ml.feature.standardscaler.StandardScalerParams
WITH_SCALING - 接口中的静态变量org.apache.flink.ml.feature.robustscaler.RobustScalerModelParams
WITH_STD - 接口中的静态变量org.apache.flink.ml.feature.standardscaler.StandardScalerParams

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